Staffing & Scheduling

Application technology for bioherbicides: challenges and opportunities with dry inoculum and liquid spray formulations.

Bioherbicides offer many potential benefits as part of an integrated weed management system or a totally biological or organic cropping system. A key factor for success is the selection of appropriate formulation and delivery systems for each target weed and cropping/climatic region. For dry inoculum products, we discuss direct implantation as an example for successful control of woody weeds, with...

Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effect has motivated the clinical use of nano-therapeutics, with mixed results on treatment outcome. High interstitial fluid pressure (IFP) has been shown ...

Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction.

Chemical shift assignment is vital for nuclear magnetic resonance (NMR)-based studies of protein structures, dynamics, and interactions, providing cru...

Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning.

In this work, we present a hardware-software solution to improve the robustness of hand gesture recognition to confounding factors in myoelectric cont...

Self-supervised pre-training with contrastive and masked autoencoder methods for dealing with small datasets in deep learning for medical imaging.

Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. T...

Multi-Adaptive Optimization for multi-task learning with deep neural networks.

Multi-task learning is a promising paradigm to leverage task interrelations during the training of deep neural networks. A key challenge in the traini...

Leveraging ChatGPT for ophthalmic education: A critical appraisal.

In recent years, the advent of artificial intelligence (AI) has transformed many sectors, including medical education. This editorial critically appra...

Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network.

Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It is one of the major factors increasing the risk o...

How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.

Over the past decade, the use of deep learning has been widely increasing in the medical image diagnosis field. Deep learning-based methods' (DLMs) pe...

Characterizing the Stability of Angiotensin II in 0.9% Sodium Chloride Using High Performance Liquid Chromatography and Liquid Chromatography Tandem Mass Spectrometry.

The purpose of this study was to evaluate the stability of angiotensin II in 0.9% sodium chloride for up to 5 days. We prepared angiotensin II dilut...

Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel.

This work addresses the quasi-synchronization of delay master-slave BAM neural networks. To improve the utilization of channel bandwidth, a dynamic ev...

Learning Skill Training Schedules From Domain Experts for a Multi-Patient Multi-Robot Rehabilitation Gym.

A robotic gym with multiple rehabilitation robots allows multiple patients to exercise simultaneously under the supervision of a single therapist. The...

Analysis of learning the bimanual control of (tele)operating joint space controlled robotic arms with 4 degrees of freedom using the two-timescales power law of learning.

Training costs for operators of robotic arms in forestry and construction are high. A systematic analysis of skill development can help to make traini...

Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space.

Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurology, cardiology, and emerging medical fields. The su...

Research on a New Rehabilitation Robot for Balance Disorders.

The treatment of patients with balance disorders is an urgent problem to be solved by the medical community. The causes of balance disorders are diver...

Artificial intelligence for dementia prevention.

INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possibl...

Deep graph convolutional network for small-molecule retention time prediction.

The retention time (RT) is a crucial source of data for liquid chromatography-mass spectrometry (LCMS). A model that can accurately predict the RT for...

Plantar somatosensory restoration enhances gait, speed perception, and motor adaptation.

Lower limb loss is a major insult to the body's nervous and musculoskeletal systems. Despite technological advances in prosthesis design, artificial l...

Improving radiology workflow using ChatGPT and artificial intelligence.

Artificial Intelligence is a branch of computer science that aims to create intelligent machines capable of performing tasks that typically require hu...

Potential Applications and Impact of ChatGPT in Radiology.

Radiology has always gone hand-in-hand with technology and artificial intelligence (AI) is not new to the field. While various AI devices and algorith...